Mobile platform continuous authentication scheme based on gait characteristics by Li YANG, Zhuoru MA, Chenghui ZHANG, Qingqi PEI

“…The popularity of smart phones renders people extremely high requirements for safety.But the traditional one-time authentication method can’t continuously guarantee the security of equipment.To solve the problem,a continuous authentication scheme based on gait characteristics was proposed to realize the identification of current visitors.Moving average filtering,threshold-based useful information interception method and other operations were adopted to reduce noise interference.Template interception was used to maximize the utilization of information,and an optimal combination of time domain features and frequency domain features were proposed to reduce the storage space requirement of users’ information.Finally,the support vector machine realized the identity authentication function.Experiments show that the proposed scheme can effectively authenticate the identities of visitors.…”
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Saturated Interference in SAR: Theoretical Analysis and Suppression Solutions by Lunhao Duan, Xingyu Lu, Jianchao Yang, Huizhang Yang, Shiyuan Zhang, Guanqi Tong, Ke Tan, Zheng Dai, Hong Gu

“…While significant research has been conducted on SAR interference suppression using parametric, nonparametric, semiparametric methods, and machine learning, these studies often neglect the impact of high-power interference, which can saturate SAR receivers due to their limited dynamic range. …”
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Application and prospect of artificial intelligence in empowering the operation and managment of oil and gas pipelines by Qi LIAO, Chunying LIU, Jian DU, Hao LAN, Yongtu LIANG, Haoran ZHANG

“…Additionally, by creating tag views of high-frequency key words of the collected literature, a detailed examination of the literature was performed from four branches of AI: expert systems, fuzzy logic, neural networks, and machine learning, to reveal the application domains, hotspots, and development trends of AI techniques. …”
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Multiple patterns of EEG parameters and their role in the prediction of patients with prolonged disorders of consciousness by Hui Li, Hui Li, Hui Li, Linghui Dong, Linghui Dong, Linghui Dong, Wenlong Su, Wenlong Su, Ying Liu, Ying Liu, Zhiqing Tang, Zhiqing Tang, Xingxing Liao, Xingxing Liao, Junzi Long, Junzi Long, Xiaonian Zhang, Xinting Sun, Hao Zhang, Hao Zhang, Hao Zhang, Hao Zhang

“…Patients were followed up for 6 months. A combination of machine learning and SHapley Additive exPlanations (SHAP) were used to develop predictive model and interpret the results.ResultsThe results indicated significant abnormalities in low-frequency spectral power, microstate parameters, and amplitudes of MMN and P3a in MCS and UWS. …”
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Predictors of Successful Testicular Sperm Extraction: A New Era for Men with Non-Obstructive Azoospermia by Aris Kaltsas, Sofoklis Stavros, Zisis Kratiras, Athanasios Zikopoulos, Nikolaos Machairiotis, Anastasios Potiris, Fotios Dimitriadis, Nikolaos Sofikitis, Michael Chrisofos, Athanasios Zachariou

“…The potential role of artificial intelligence and machine learning in enhancing predictive models was also explored. …”
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Impact of different auditory environments on task performance and EEG activity by Zhen Xue, Wenxiao Zhong, Yong Cao, Shuang Liu, Xingwei An

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In-flight Electrocardiography Monitoring in a Pilot During Cross Country Flight by William D. Kim, Sang-Wook Kim, Seong-Kyu Cho, Ju Hyeon Byeon, GunYoung Lee, WooSeok Hyun, JoungSoon Jang

“…Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Methods: In this study, continuous ECG activity was recorded of one pilot who flied as a pilot flying during a 4-hour long round trip using wearable ECG machine and was analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). …”

Adaptive respiratory muscle trainer based on hybrid nanogenerator sensor and artificial intelligence by Ziao Xue, Puchuan Tan, Jiangtao Xue, Yuan Xi, Minghao Liu, Yang Zou, Qiang Zheng, Zhou Li, Yuxiang Wu

“…This hybrid sensor can simultaneously collect both high‐frequency and low‐frequency signals generated by the Karman vortex street effect with low hysteresis. …”
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Substantiation of the Line for the Primary Processing of Industrial Hemp lnto Hemp of the Same Type Undirected by E. V. Novikov, I. N. Altukhova, A. V. Bezbabchenko

“…Levitsky and two shaking machines with a lower combed field at the rotation frequency of a disintegrator rotor of 1000 revolutions per minute, and a swing frequency of the shaking machine needle rollers of 230 revolutions per minute. …”
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Theoretical and Experimental Study of the Effects of Impact Drilling Parameters on the Properties of Surrounding Rock Damage by Zhi Liu, Wanrong Wu, Qianhua Hao, Peng Sun, Yuangen Ding

“…. × 200 mm) containing central axial holes formed either by impact or nonimpact drilling methods were tested in uniaxial compression to failure on an Instron 1346 universal testing machine to investigate their mechanics and damage properties. …”
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Civil Aircraft Landing Attitude Ultra-Limit Warning System Based on mRMR-LSTM by Fei Lu, Tong Jing, Chunsheng Xie, Haonan Chen

“…Subsequently, through data pretreatment methods such as data cleaning, frequency normalization, data standardization, and feature classification, the experimental dataset is transformed into a form recognizable by machine learning algorithms and neural network models. …”
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Evaluating the Effects of Three High Intensity Interval Training Protocols on Maximum Oxygen Consumption and Leg Strength in Recreational Football Athletes by Wirat Sonchan, Saralee Sonchan, Ratanyoo Longrak

“…The training programs spanned 6 weeks with a frequency of 3 sessions per week on non-consecutive days. …”
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A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques by Rizal Bakri, Bobur Sobirov, Niken Probondani Astuti, Ansari Saleh Ahmar, Pawan Kumar Singh

“…Traditional segmentation methods such as K-means are often used, but they have limitations in capturing the flexibility of school characteristics. …”
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Balancing Efficiency and Efficacy: A Contextual Bandit-Driven Framework for Multi-Tier Cyber Threat Detection by Ibrahim Mutambik, Abdullah Almuqrin

“…In response to the rising volume and sophistication of cyber intrusions, data-oriented methods have emerged as critical defensive measures. …”
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Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models by Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu

“…Experimental results reveal that language models, particularly XLNet, outperform traditional approaches that combine term frequency–inverse document frequency features with support vector machine or utilize deep models like HAN. …”
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Active Power Oscillation Property Classification of Electric Power Systems Based on SVM by Ju Liu, Wei Yao, Jinyu Wen, Haibo He, Xueyang Zheng

“…Twenty sampling points of the envelope curve are selected as the feature matrices to train and test the supporting vector machine (SVM). The tests on the 16-machine 68-bus benchmark power system and a real power system in China indicate that the proposed oscillation classification method is of high precision.…”
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Evaluation of Floods and Landslides Triggered by a Meteorological Catastrophe (Ordu, Turkey, August 2018) Using Optical and Radar Data by Sultan Kocaman, Beste Tavus, Hakan A. Nefeslioglu, Gizem Karakas, Candan Gokceoglu

“…The results presented here show that considering the occurrence frequency and immense damages after such events, the use of novel remote sensing technologies and spatial analysis methods is unavoidable for disaster mitigation efforts and for the monitoring of environmental effects. …”
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A Global Irradiance Prediction Model Using Convolutional Neural Networks, Wavelet Neural Networks, and Masked Multi-Head Attention Mechanism by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Salah Hannechi

“…Existing approaches, including statistical methods, conventional machine learning models, and standalone deep learning techniques like LSTM, fail to integrate local features and long-term dependencies simultaneously, creating a need for more robust solutions. …”
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Applying model-based recursive partitioning to improve pedestrian exposure models to support transportation safety analyses by Jakob Wiegand, Vikash Gayah

“…The MBRP approach combines traditional statistical methods (e.g. NB regression) with recursive data partitioning techniques commonly found in tree-based machine learning methods. …”
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A Weakly Supervised and Self-Supervised Learning Approach for Semantic Segmentation of Land Cover in Satellite Images with National Forest Inventory Data by Daniel Moraes, Manuel L. Campagnolo, Mário Caetano

“…National Forest Inventories (NFIs) provide valuable land cover (LC) information but often lack spatial continuity and an adequate update frequency. Satellite-based remote sensing offers a viable alternative, employing machine learning to extract thematic data. …”
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